🙋♀️ About Me
I am a third-year Ph.D. candidate in the School of Computing and Data Science (HKU-CDS) at the University of Hong Kong (HKU), advised by Prof. Reynold Cheng.
My research focuses on AI-native data systems and reusable intelligence for agent systems, including query processing over learned and structured relationships, graph hypothesis testing, and agent orchestration with memory retrieval.
I collaborate with Prof. Sihem Amer-Yahia (CNRS, France) and Prof. Laks V.S. Lakshmanan (UBC). I expect to graduate in August 2027. Feel free to reach out via email.
🔬 Research Interests
AI-native Data Systems
- graph hypothesis testing
- query processing over learned and structured relationships
Reusable Intelligence for Agents
- agent experience / memory retrieval
- agent orchestration
- inference-time decision making
🔥 News
- 2026.03: Invited talk at Laboratoire d’Informatique de Grenoble (LIG), hosted by Prof. Sihem Amer-Yahia.
- 2026.03: Silver Medal, 51st International Exhibition of Inventions Geneva.
- 2025.11: 🎉🎉 Research paper accepted at SIGMOD 2026.
- 2025.06: GRF proposal funded (Graph Hypothesis Testing).
- 2024.06: Research paper accepted at VLDB 2024.
- 2024.03: Demo paper accepted at WWW 2024.
- 2023.05: Paper accepted at CITERS 2023 (AI for Education).
📝 Publications
My publications focus on reliable querying and decision-making, spanning from different types of resource constraints, including limited data access, imperfect data representations, and expensive computation.
On Efficient Approximate Aggregate Nearest Neighbor Queries over Learned Representations
Carrie Wang, Sihem Amer-Yahia, Laks V. S. Lakshmanan, Reynold Cheng
Introduces Aggregate Queries over Nearest Neighbors (AQNNs) and a framework, SPRinT, for cost-efficient aggregate querying over neighborhoods induced by learned representations.
A Sampling-based Framework for Hypothesis Testing on Large Attributed Graphs
Carrie Wang, Chrysanthi Kosyfaki, Sihem Amer-Yahia, Reynold Cheng
Formulates hypothesis testing over attributed graphs as a statistical query processing problem and develops a framework for it and a hypothesis-aware graph sampler PHASE.
HINCare: An Intelligent Helper Recommender System for Elderly Care
Carrie Wang, Wentao Ning, Xiaoman Wu, Reynold Cheng
CITERS 2023Algorithms for Enabling and Verifying Upskilling, Sihem Amer-Yahia, Reynold Cheng, Nassim Bouarour, Carrie WangKnowledge-Based Systems 2023Using a novel clustered 3D-CNN model for improving crop future price prediction, Liege Cheung, Carrie Wang, Adela S M Lau, Rogers M C Chan
💻 Research Experience
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Research Intern, Huawei Hong Kong Research Center (HKRC), 2012 Laboratory
Jun 2025 – Oct 2025
Work on probabilistic user behavior modeling and spoof fingerprint detection. -
Participant, The 6th ACM Europe Summer School on Data Science
Jun 2025
Best Lightning Talk Award (Top 4/42). -
Visiting Researcher, Laboratoire d’Informatique de Grenoble (LIG), CNRS
May 2024 – Jun 2024
👩🏫 Teaching Experience
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Fall 2024Teaching Assistant, Introduction to Database Management Systems
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Spring 2024Teaching Assistant, Big Data Management
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Fall 2020Teaching Assistant, Probability and Statistics I
📖 Education
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Ph.D. in Computer Science, School of Computing and Data Science, HKU
2023.09 – 2027.08 (expected) -
B.Sc. in Mathematics and Decision Analytics, School of Computing and Data Science, HKU
2018.09 – 2023.01
🎖 Honors and Awards
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2026Silver Medal in 51st International Exhibition of Inventions Geneva
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2023–2027HKU Postgraduate Scholarship
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2023First Class Honors
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2020–2021Yu Kam Tim Chan Siu Hing Award in Artificial Intelligence and Data Science
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2018–2022HKU Foundation Entrance Scholarship
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2019–2022Dean’s Honors List
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2017–2018First Prize, MOMENTUM Social Innovation Contest
🧩 Academic Service
Reviewer: WSDM 2026, CIKM 2026
Student Volunteer: ICDE 2025